Diabetes Prediction Using PySpark MLlib

A collection of small data science projects to predict house pricing for two different datasets

12 year nutrient intake analysis across financial classes with PySpark and KMeans clustering

PySpark is a Python API for support Python with Spark. Whether it is to perform computations on large datasets or to just analyze them

A docker hosted australian weather prediction analysis with PySpark and Hadoop DFS

Predicting House Prices using Linear Regression, Random Forest and GBT Regression

Model to predict whether we should approve a credit card application.

An introduction to PySpark, Creating a simple multi regression ML model and hosting it on a databricks cluster

Analyzing crime in Chicago using large scale computing methods

In the project, a linear regression model is trained on California housing data in 1990. The goal is to predict the median value of a house in a residential area. The metrics RMSE, MAE and R2 are used to assess the quality of the model. As well as pyspark/mllib methods were used.

Projeto da 2º Edição do Challenge Data Science da Alura, onde utilizei o PySpark para analisar e tratar os dados dos preços de imóveis do Rio de Janeiro.

A simple implementation of MLLIB of PySpark to solve a Machine Learning Problem.

doing health insurance analytics and prediction at scale with pyspark.

Python Spark Pyspark Big Data RDD operations

Pyspark Tutorial on azure databricks

Predicting Machine failure using Machine learning on a synthetic dataset of an existing milling machine consisting of 10,000 data points

Ce projet est un projet orienté analyse et prédiction du comportement client en utilisant la technologie spark apache avec tout ces composants d'analyse, prédiction, régression, forêt... en fonction des achats, produits, région, sexe...

Predictive analytics with Spark